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Sustainable water management under future uncertainty with eco-engineering decision scaling


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Managing freshwater resources sustainably under future climatic and hydrological uncertainty poses novel challenges. Rehabilitation of ageing infrastructure and construction of new dams are widely viewed as solutions to diminish climate risk, but attaining the broad goal of freshwater sustainability will require expansion of the prevailing water resources management paradigm beyond narrow economic criteria to include socially valued ecosystem functions and services. We introduce a new decision framework, eco-engineering decision scaling (EEDS), that explicitly and quantitatively explores trade-offs in stake- holder-defined engineering and ecological performance metrics across a range of possible management actions under unknown future hydrological and climate states. We illustrate its potential application through a hypothetical case study of the Iowa River, USA. EEDS holds promise as a powerful framework for operationalizing freshwater sustainability under future hydrologi- cal uncertainty by fostering collaboration across historically conflicting perspectives of water resource engineering and river conservation ecology to design and operate water infrastructure for social and environmental benefits.
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Securing the supply and equitable allocation of fresh water to
support human well-being while sustaining healthy, functioning
ecosystems is one of the grand environmental challenges of the
twenty-rst century, particularly in light of accelerating stressors
from climate change, population growth and economic develop-
ment. Rehabilitation of ageing infrastructure and construction of
new infrastructure are now widely viewed as engineering solutions
to mitigate future climatic uncertainty in the hydrologic cycle1.
Indeed, the construction of tens of thousands of dams in the twen-
tieth century helped secure water supplies and fuel economic devel-
opment in industrialized countries, and developing economies are
now pursuing massive new infrastructure projects with thousands
of new dams proposed for hydropower production and water sup-
ply security 2.
Despite the economic stimulus provided by many dams histori-
cally, the global experience with dam building warns that traditional
approaches to water infrastructure development in a rapidly chang-
ing world carry severe risks of economic and environmental failure.
First, large water projects are very capital-intensive and long-lived,
costing billions of dollars to plan, build and maintain. Yet, they
are vulnerable to biased economic analyses3, cost overruns and
construction delays, and changing environmental, economic and
social conditions that can diminish projected benets4,5. Under a
variable and changing climate, large water infrastructure may even
risk becoming stranded assets6. Second, the principles of economic
eciency inherent in cost-benet analysis dominate project design
and performance assessment, making integration of social and
environmental benets and costs into a comprehensive economic
Sustainable water management under future
uncertainty with eco-engineering decision scaling
N. LeRoy Po1*, Casey M.Brown2, TheodoreE.Grantham3, John H.Matthews4, Margaret A. Palmer5,
Caitlin M. Spence2, Robert L. Wilby6, Marjolijn Haasnoot7,8, Guillermo F. Mendoza9,
Kathleen C. Dominique10 and Andres Baeza11
Managing freshwater resources sustainably under future climatic and hydrological uncertainty poses novel challenges.
Rehabilitation of ageing infrastructure and construction of new dams are widely viewed as solutions to diminish climate risk,
but attaining the broad goal of freshwater sustainability will require expansion of the prevailing water resources management
paradigm beyond narrow economic criteria to include socially valued ecosystem functions and services. We introduce a new
decision framework, eco-engineering decision scaling (EEDS), that explicitly and quantitatively explores trade-os in stake-
holder-defined engineering and ecological performance metrics across a range of possible management actions under unknown
future hydrological and climate states. We illustrate its potential application through a hypothetical case study of the Iowa
River, USA. EEDS holds promise as a powerful framework for operationalizing freshwater sustainability under future hydrologi-
cal uncertainty by fostering collaboration across historically conflicting perspectives of water resource engineering and river
conservation ecology to design and operate water infrastructure for social and environmental benefits.
evaluation a signicant challenge7,8. ese costs can be substantial,
as evidenced by human displacement5,9, local species extinctions10
and the loss of ecosystem services such as oodplain sheries and
other amenities11,12.
As unanticipated economic, social and environmental costs
accumulate with ageing water infrastructure, society is investing
in restoration projects to partially undo longstanding environmen-
tal degradation, including modifying ow releases from dams13,14
and, in some cases, dam removal15. As global-scale impairment
of aquatic ecosystem function becomes increasingly documented
and articulated16,17, there is urgent need for a broader conception
of sustainable water resource management that formulates environ-
mental health as a necessary ingredient for water security and the
social well-being it supports18–20. Notably, new national directives
are emerging to develop and manage river ecosystems in more envi-
ronmentally sustainable ways that retain social benets, including
in the USA21, Europe22,23 and Australia24.
Towards a sustainable water management paradigm
Here, we ask if a more sustainable water management philosophy
can be forged to guide investment in, and design of, water infra-
structure while avoiding adverse (and sometimes irreversible) social
and environmental consequences. We consider ‘sustainable water
management systems’ to be those that meet the needs of society
over the lifetime of the infrastructure while also maintaining key
ecological functions that support the long-term provision of eco-
system goods, services and values, including biodiversity mainte-
nance. ese systems would embrace the principle of resilience, that
1Department of Biology and Graduate Degree Program in Ecology, Campus Mail 1878, Colorado State University, Fort Collins, Colorado 80523, USA.
2Civil and Environmental Engineering, University of Massachusetts, 12B Marston Hall, 130 Natural Resources Road, Amherst, Massachusetts 01003,
USA. 3US Geological Survey, Fort Collins Science Center, 2150 Centre Avenue, Building C, Fort Collins, Colorado 80526, USA. 4Alliance for Global Water
Adaptation, 7640 NW Hoodview Circle, Corvallis, Orlando 97330, USA. 5National Socio-Environmental Synthesis Center, University of Maryland, 1 Park
Place, Annapolis, Maryland 21401, USA. 6Department of Geography, Loughborough University, Leicestershire, LE11 3TU, UK. 7Deltares, Department
of Scenarios and Policy Analysis, PO Box177, 2600MH, Delft, The Netherlands. 8Delft University of Technology, Faculty of Technology, Policy &
Management, PO Box5015, 2600GA, Delft, The Netherlands. 9US Army Corps of Engineers, Institute for Water Resources, 7701 Telegraph Road,
Alexandria, Virginia 22315,USA. 10Organisation for Economic Co-operation and Development (OECD), 2rue André-Pascal, 75775 Paris, France. 11National
Socio-Environmental Synthesis Center, 1 Park Place, Annapolis, Maryland 21401,USA. *e-mail: NLeRoy.Po
© 2015 Macmillan Publishers Limited. All rights reserved
is, the capacity to persist with functional integrity under changing
social and environmental conditions25. Indications of this emerging
perspective are reected in calls for greater focus on demand-side
management, rather than supply-side solutions26, as well as ‘green
infrastructure approaches, such as ‘so-path’ solutions27 and man-
aged natural systems28. Deep uncertainty about future climate raises
signicant concerns about how to achieve long-term economic
benets and performance reliability of major water projects29,30.
is unprecedented uncertainty renders traditional approaches to
the design of long-lived infrastructure inadequate, requiring new
decision-making approaches31. In the context of a changing (non-
stationary) hydrologic cycle, incorporation of alternative design
and management principles can be viewed as reducing risk in infra-
structure investment by enhancing ‘robustness’ (satisfactory per-
formance under a wide range of uncertain futures) and ‘adaptive
capacity’ (the ability to be modied rapidly and economically in
response to changing, unforeseen conditions)32,33.
Planning for resilient, robust and adaptive water infrastructure
to achieve social, economic and environmental objectives under a
highly uncertain future presents novel challenges. First, contrast-
ing paradigms in water resource engineering and in conservation
ecology have dominated the broader societal debate about infra-
structure design and operation over the past several decades34,35,
and these perspectives have typically been antagonistic. However,
the elds of water resource engineering and conservation ecol-
ogy are now independently re-examining long-held, foundational
assumptions, in no small part because of concerns about climate
change and other forms of non-stationarity (Box1). ese philo-
sophical shis are subsequently creating the possibility of revisiting
ingrained presumptions about barriers to collaboratively attaining
more sustainable water resource management. Second, methods for
integrating ecological principles into water infrastructure design
and operation to satisfy multiple objectives have been proposed8 but
are not well established in practice36,37. e key question emerges
of how to operationalize sustainable water management to couple
engineering design principles with ecosystem requirements in the
context of non-stationary stressors (for example, changes in climate,
water use, population growth and land-use change).
A new analytical framework to climate adaptation planning
has emerged that aims to facilitate the sustainability dialogue
between water resource engineers and conservation ecologists. is
approach, called decision scaling38,39, was developed as an alter-
native to prevailing top-down climate risk assessment methods
in the water resources community that rely on projecting climate
conditions several decades into the future to assess risk, primarily
through the use of global circulation models (GCMs). GCM pro-
jections, however, have large, irreducible uncertainties40 and poor
capability of representing climatic variability (for example, storm
intensity-duration-frequencies) that water resource engineers
require to design water infrastructure41,42. us, GCMs are oen of
limited use to water resource planners and decision makers attempt-
ing to understand and mitigate climate risks in the immediate to
mid-term management future43,44.
Decision scaling, by contrast, is a bottom-up risk assessment
approach that engages decision makers by starting with stakeholder-
determined metrics that dene acceptable system performance.
System vulnerability is then assessed by evaluating the sensitivity
of metrics (for example, ability to meet a water delivery target) to
a variety of non-stationary threats, such as climate change, demo-
graphic change and economic trends that occur over management-
relevant timescales. e decision scaling approach has been applied
to evaluate climate risks to water management systems focused on
engineering performance indicators, such as water supply reliabil-
ity38, ood risk estimation45 and cost-benet analysis46, as well as
climate-sensitive hydrologic indicators47.
As in the water resources arena, ecosystem management is
increasingly focused on reducing the vulnerability of sensitive
species, ecological processes and natural resource production to
a variety of non-stationary stressors through risk analysis48 and
stakeholder-driven processes49. For example, in regulated rivers,
environmental ows to sustain desired ecological processes or con-
ditions downstream of dams are oen dened through vulnerability
assessments involving scientists, government agencies and water
users50. Similarly, ‘smart licenses’ are being devised to protect the
stakeholder-dened needs of both the environment and water users
under anticipated climate variability and change51. More broadly,
formal decision frameworks, such as structured decision making52,
are being adopted by natural resource agencies to identify critical
ecological thresholds and guide adaptive management to achieve
sustainable outcomes. us, decision scaling is consistent, in terms
of process and scope, with bottom-up approaches that ecosystem
managers are familiar with and oen rely on for decision making.
Eco-engineering decision scaling
Expansion of the existing decision scaling framework to consider
both engineering and ecological performance aords a powerful
Rapid climate change, population growth and economic trends
are generating unprecedented uncertainty about how to achieve
sustainability targets for water management and ecosystem con-
servation, as well as simultaneous opportunities to nd common
ground. First, traditional water resource engineering is strug-
gling with climate non-stationarity (unknowable uncertainty
about future hydrologic conditions) and seeking new approaches
to guide infrastructure planning and avenues for secure eco-
nomic investment under a wide range of climate scenarios77.
Second, climate variability and change plus the pervasive eects
of human activities on ecosystems are broadly challenging con-
servation and restoration ecology, which have traditionally
dened ecosystem management targets by reference to historical
(‘natural’) conditions and focused on habitat reserve strategies78.
Emerging perspectives in aquatic ecology now place biological
conservation in the context of highly altered and non-stationary
hydrosystems that require active management within human-
dominated landscapes to sustain critical ecosystem functions79–81.
ese perspectives align with a broader conservation approach
of “managing for resilience”82, which focuses on maintaining
key processes and relationships in social-ecological systems so
that they are robust against a wide range and variety of pertur-
bation from climate or other stressors. is paradigm repre-
sents a departure from traditional conservation biology in that
it emphasizes the endurance of system-wide properties (rather
than a sole focus on individual species) and promotes reconcilia-
tion of conservation objectives with the alteration of natural sys-
tems by human inuences81,83. Together, emerging paradigms in
ecology and engineering are giving rise to potential new levels
of cooperation and communication across these (traditionally
conicting) disciplines. For example, ecologists are now devel-
oping socially contextualized conservation tools to inform water
infrastructure management (‘environmental ows50,84,85) and
water resource engineers are actively exploring how to incorpo-
rate these into infrastructure operations86,87 with implications for
multiple objective evaluation approaches8,88.
Box 1 | Shifting paradigms in water resource engineering and conservation ecology.
© 2015 Macmillan Publishers Limited. All rights reserved
new analytical approach to operationalize sustainable water resource
management in the face of future hydrologic uncertainty. We refer
to the integrated analysis of these complementary domains as eco-
engineering decision scaling (EEDS), and it builds from the multi-
ple-objective decision scaling approach used for policy evaluation
in the International Upper Great Lakes Study53,54. e conceptual
signicance of EEDS is that it allows explicit evaluation of trade-os
between engineering design features and socially valued ecological
performance associated with water resource development. More
specically, this trade-o analysis occurs in the initial stages of pro-
ject development, so that economic, engineering and ecological vul-
nerabilities can be simultaneously compared. Such early evaluation
of ecosystem vulnerability is necessary to reveal a range of poten-
tial design and management options in complex social-ecological
systems55. is new approach is closely aligned with planning
principles that engineers oen follow, such as the Principles and
Guidelines used by the US Army Corps of Engineers (USACE)56,
and similar guidance documents in Europe57.
e EEDS framework signicantly contrasts with approaches
typically used to assess the environmental impacts of water infra-
structure projects, and it can be summarized as a ve-step pro-
cess shown visually in Fig. 1 and described in detail in Box 2.
Traditionally, initial project conception and design are driven by
economic assessment of expected direct costs (for example, nanc-
ing, construction and maintenance) and benets (for example, rev-
enue from hydropower production and water supply or avoided
damages). Typically, several competing economically viable alter-
natives are developed in engineering designs before environmental
impacts are considered. In the EEDS approach, however, both
engineering and environmental performances are quantied and
simultaneously compared across management alternatives under
the range of future uncertainty. Ecological performance indicators
must be clearly dened and quantitative, but signicantly, they need
not be monetized (which is oen challenging or infeasible58) to allow
comparison with traditional economic indicators. Furthermore,
the EEDS approach can accommodate multiple performance met-
rics representing a diverse suite of economic, social and ecological
objectives (for example, ref.8). For the sake of simplicity, we present
only two metrics in our conceptual framework (Fig.1) and three
metrics in our case study below. Ultimately, stakeholders assess
viable decision pathways based on the aggregate performance of all
metrics and implement management options according to values
and preferences.
Iowa River case study
We illustrate the EEDS framework through a hypothetical exam-
ple of a water resource decision problem for an existing ood man-
agement project. Coralville Dam was constructed in 1958 by the
USACE on the Iowa River to protect Iowa City and downstream
farmlands from ooding (Fig. 2). Iowa City also has a series of
oodplain levees in place to reduce ood risk. Since 1990, several
severe runo events have resulted in unscheduled water releases
from the dam spillway, raising concerns that extreme oods are
becoming more frequent and that current management operations
are inadequate for controlling ood risk. We apply EEDS to evaluate
the potential economic costs associated with altered climate regimes
Step 1: Define system performance criteria Step 2: Build systems model
Systems model
Climate Land use
Hydrologic model
Water use
Water infrastructure model
engr & ecol performance
x1, x2
engr > θ1 is unacceptable
ecol > θ2 is unacceptable
Consider managements options:
O1, O2 and O3
Step 3: Conduct vulnerability analysis
Step 5: Identify preferred decision and, if necessary,
re-evaluate management options and/or criteria
Step 4: Evaluate options to inform decision(s)
Figure 1 | The five steps of eco-engineering decision scaling (EEDS). See main text and Box 2 for a detailed description of each step.
© 2015 Macmillan Publishers Limited. All rights reserved
that increase ood risk and explore how alternative ood-control
management strategies could aect both engineering and ecological
performance indicators. Extensive data on dam operations, system
hydrology and ood inundation risk (Supplementary Information)
make the system amenable to a hypothetical exploration of EEDS in
a plausible management scenario.
Identication of performance indicators, acceptability thresh-
olds and decision options (step1, Fig. 1). We begin by dening
stakeholder interests as chiey concerned with minimizing eco-
nomic damages from ooding and with maintaining key ecologi-
cal functions of the downstream aquatic and riparian ecosystems.
Coralville Dam is primarily a ood-control project, and stakehold-
ers receive economic benets from ood protection in the form of
avoided ood damages. We use estimated annual costs (EAC) from
ood damage as our engineering performance metric to evaluate
costs of alternative decision options (Supplementary Table1). We
assume stakeholders are willing to pay up to 1.5-times the long-
term average costs (1959–2010) for the benet of avoiding ood
damages. is threshold is a 50% increase in historical average
EAC to allow for reasonable future management costs (for example,
building levees and reimbursing crop loss) that were not used when
calculating the current EAC.
e assessment of ecological performance is focused on key fac-
ets of the ow regime of known ecological importance59,60. First, we
consider high ows that inundate oodplains thereby providing
shallow, low-velocity and highly productive habitat for freshwater
organisms12. Many sh species time their spawning with oodplain
inundation, and their young take advantage of nutrient-rich ood-
plain habitats before entering the river channel61. e periodic inun-
dation of oodplains is also essential to the health of riparian plant
communities62. ese ecological functions can be provided when
oodplains are inundated for an extended period of time, generally
up to several weeks per year. Second, we consider the rate of ow
uctuations caused by water releases from the dam, which aects the
availability and variation of in-channel habitat downstream. When
articially increased by reservoir release operations, uctuating ows
can adversely aect sh and other aquatic organisms63.
We dened two ecological performance metrics for our case
study. A oodplain performance threshold was set as the histori-
cal annual average of oodplain area that is inundated for at least
seven consecutive days, derived from estimated relationships
e EEDS framework comprises ve distinct and iterative steps
(Fig. 1). Step1 is a stakeholder-driven process to identify a set
of possible management decision options (for example, O1, O2
and O3 in Fig.1), performance indicators (for engineering, engr,
and ecology, ecol) and user-specied thresholds (θ1 and θ2) that
dene conditions under which the system no longer performs at
an ‘acceptable’ level. Performance indicators represent key system
values or services important to stakeholders. In the engineering
domain, performance criteria could include, for example, reli-
ability of water supply, reduction in expected ood damage, or
the internal rate of return for a proposed project. Ecological per-
formance metrics are also identied to represent desirable envi-
ronmental conditions or ecosystem services. Such performance
criteria could include maintaining a minimum population size for
target species, or sustaining a specied areal coverage of riparian
forests via overbank ows. Other metrics representing important
ecosystem processes, such as ood regimes or sediment trans-
port dynamics, could also be selected, depending on the nature
of the study system, stakeholder preferences and data availabil-
ity. Similarly, more spatially extensive metrics, such as connec-
tivity among river segments, could be developed for multiple
infrastructure components, such as siting of dams throughout a
river network.
Step 2 in EEDS requires development of a systems decision
model that relates changes in climate and other stressors (for
example, population growth, shis in water demand and land-use
change) to engineering and ecological performance outcomes.
is would typically be implemented through any of several inte-
grated water management models, such as the Water Evaluation
and Planning (WEAP) system89, or by linking basin hydrologic
models (for example, the Variable Inltration Capacity (VIC)
model90 and the Distributed Hydrology-Soil-Vegetation Model
(DHSVM)91) with water management operating rules to calculate
resultant performance indicators. A systems decision model pro-
vides the basis for evaluating the consequences of management
options across a wide range of plausible values in key climate vari-
ables and other system stressors (x1 and x2 in Fig.1).
In Step3, a vulnerability analysis (stress test45) is performed
to exhaustively evaluate how the engineering and ecologi-
cal performance indicators of the system respond to changes in
climate or other input parameters (that is, the x1 and x2 variables).
Performance indicators can be mapped visually in a plausible
climate space (see Supplementary Information for details) to
identify the conditions under which the system fails to satisfy
both engineering and ecological indicators. e sensitivity of the
system to input and model parameters can also be explored to
identify variables and sources of uncertainty that have the great-
est inuence on performance outcomes35. For example, an assess-
ment of system vulnerability to a wide range of plausible states
may reveal that non-climate factors (such as population growth
and shis in water demand) are of greater concern than potential
changes in climate variability.
e approach can also highlight combinations of specic
changes that lead to failure, such as a given magnitude of warming
and drying. en, the acceptability of a particular decision can
be assessed according to the degree to which the engineering and
ecological performance indicators are mutually satised over a
spectrum of plausible future conditions.
In Step4, alternative management options can be specied in
the systems model to evaluate how the multiple domains of accept-
able performance and their mutual overlap vary among the avail-
able management options. e option with the greatest overlap in
the domains of acceptable performance among chosen indicators
would be considered as the most robust and sustainable in the face
of future uncertainty. In this way, decisions are assessed according
to their ability to provide mutually robust performance, that is,
satisfy both the engineering system and ecosystem performance
indicators over the widest range of future uncertain conditions.
Finally, in Step 5, decision makers (stakeholders and policy
makers) assess the feasibility of either moving forward with the
most promising option or developing new options that may bet-
ter satisfy objectives, thus reiterating the process. Decision makers
may also decide to consider alternative performance metrics or
preference thresholds for re-evaluation. Considerations that aect
the political or institutional feasibility of some options may be
dicult to incorporate into computational models, necessitating
the engagement of policy makers throughout the decision process
to ensure credible and relevant options. In this way, EEDS is an
iterative decision-making process that is consistent with emerging
adaptive and ecosystem-based water management frameworks52,92.
Box 2 | The eco-engineering decision scaling framework: an iterative five-step process.
© 2015 Macmillan Publishers Limited. All rights reserved
between discharge and oodplain area from Coralville Dam to river
mile46 of the Iowa River (Supplementary Fig.2). is threshold is
an intentionally simplied measure of oodplain function (that is,
timing of oods is not considered), and it is based on an assumed
stakeholder preference for avoiding the loss of future oodplain
functions relative to historical conditions. A second metric was
dened by the magnitude of daily changes in outows from the
reservoir during periods when ows are being released rapidly in
response to upstream inows. We calculated a ow recession rate
(dierence between consecutive daily ow magnitudes) and set a
threshold of +30% of the natural daily recession rate, that is, rela-
tive to the recession rates of unregulated inows into the reservoir
(see Supplementary Information for details). For both metrics, we
make the simplifying assumption that biological communities and
ecosystem functions will persist under future climate conditions if
ood inundation patterns are maintained and excessive ow reces-
sion rates are avoided.
Our hypothesis is that re-engineering of the current ood risk
management system could provide the opportunity both to reduce
the system’s vulnerability to ood risk associated with rapid cli-
mate change and to satisfy ecological objectives for sustaining more
resilient downstream aquatic and riparian ecosystems. By quanti-
fying the trade-o space between the economic costs of engineer-
ing design and maintenance and the environmental benets under
alternative ood-risk management strategies, we aim to identify
a robust option that meets both objectives under a wide range of
hydrological conditions in an uncertain future. To examine these
trade-os, we modelled engineering and ecological performance
metrics over a range of future climates, subject to four hypotheti-
cal management options: (1) maintain status quo (SQ), that is, cur-
rent levee height and reservoir operating rules; (2) re-operate the
reservoir (RR) by modifying existing reservoir operation rules to
allow for increased emergency ow releases during the growing sea-
son, which would increase reservoir capacity for capturing storm
runo; (3) raise existing levees (RL) to increase ood protection
around Iowa City; and (4) jointly re-operate the reservoir and raise
levees (RR+RL).
Developing the decision systems model (step2, Fig.1). We used
publicly available hydro-climatic data along with reservoir opera-
tions and hydraulic mapping data from the USACE (Supplementary
Information) to develop a water management systems model of the
Iowa River basin. We used this model to evaluate how the engi-
neering performance indicator (EAC) and the ecological indicators
(oodplain inundation area and ow recession rate) independently
respond to climate variability (Supplementary Fig. 1). A rainfall-
runo model of the basin was calibrated with historical climate
and discharge data to predict daily inows to Coralville Reservoir.
Inows were then fed into a reservoir operations model to estimate
outows to the Iowa River below the dam. Next, a river hydraulics
model was used to estimate the daily downstream inundation area
as a function of river discharge to allow estimation of annual costs
(US$), oodplain inundation and ow recession rates. e systems
model was modied for each of the four management strategies by
specifying higher levees and/or alternative reservoir operation rules.
Vulnerability analysis (steps3 and4, Fig.1). We generated a large
stochastic input series of climate data64 with altered mean tempera-
ture, mean precipitation and daily precipitation coecient of vari-
ation (Supplementary Information). Simulated data were then fed
into the decision systems model (Supplementary Fig.1) to evaluate
performance outcomes under specied management options and
climate futures. Results of the vulnerability analysis were plotted
across the range of climate variables relevant to ood risk manage-
ment. As our primary demonstration of the EEDS framework, we
evaluated how thresholds in performance indicators responded
to deviation in predicted mean annual discharge and daily
precipitation coecient of variation (CV), two hydro-climatic vari-
ables of relevance in ood forecasting. As an alternative analysis, we
explored vulnerability in a future climate space directly compara-
ble to GCM climate projections, in which system performance was
evaluated over a range of predicted mean annual temperature and
mean annual precipitation values (Supplementary Information).
Our results (Fig.3) show how changes to the two hydro-climatic
variables (displayed as orthogonal axes) aect system performance
and potentially cross stakeholder-dened vulnerability thresholds.
Each pixel represents a climate state simulated through the systems
model. e engineering indicator (EAC, rst column of Fig.3) and
the ecological indicator (oodplain inundation, second column) are
plotted in a future climate state space dened by change in aver-
age annual daily ow and the variability of the daily precipitation
series for each of the four management options. e indicators
are expressed as the magnitude of change relative to mean histori-
cal conditions. e third column in Fig.3 displays the domain of
‘mutually acceptable performance’, delineated by the white area that
satises both the acceptable EAC and oodplain inundation perfor-
mance criteria. In Fig.4, the ow recession metric (third column) is
included with the EAC and oodplain metrics to evaluate multiple-
metric responses to the four management options. e shaded plots
in the fourth column of Fig. 4 show the mutually acceptable perfor-
mance for all three indicators. e mutually acceptable space can
be quantied and, if desired, probabilities assigned65. Here, visual
inspection is sucient.
Iowa River
Coralville Lake
2008 flood
Iowa City
024812 16
Figure 2 | Iowa River study area near Iowa City, Iowa, USA. This map
shows Coralville Dam with flooding spillways and the extent of the 2008
flood that breached some levees in Iowa City (urban footprint shown in
grey) and extensively inundated downstream floodplain farmland and
riparian habitats (dark blue).
© 2015 Macmillan Publishers Limited. All rights reserved
Evaluation of trade-o space with alternative decision options
(steps4 and5, Fig.1). We evaluate the premise that the system can
be managed to meet both engineering and ecological objectives by
examining the independent and joint responses of performance
metrics to the dierent management options in Figs3 and4.
Figure3 shows that for all four management options, the EAC
metric is more likely to exceed the acceptable threshold level
(dashed line) as precipitation CV increases (more frequent, large
oods) and as average annual ow increases (wetter conditions).
e oodplain performance indicator shows the reverse pattern,
with wetter, more variable precipitation leading to greater ood-
plain inundation. Superimposing the EAC and oodplain inun-
dation response surfaces reveals a domain of mutually acceptable
performance (white space in the third column of Fig.3). e SQ
management strategy aords little overlap in mutually acceptable
climate space. Similarly, the RR strategy has virtually no eect
on the system’s engineering performance relative to SQ. ere is,
however, a slight contraction in the climate space associated with
catastrophic ood damages, that is, those that are most expensive
(for example, ≥4 times the historical EAC).
In contrast, the ecological oodplain performance indicator
is signicantly enhanced under the RR strategy, with oodplain
inundation areas greater than mean historical conditions for all but
the driest and least variable of simulated climate futures. e RL
management action greatly reduces the vulnerability to unaccepta-
ble ood damage relative to SQ, yet it has no detectable eect on
oodplain inundation. Only under wetter, more variable climates
would oodplain inundation exceed the performance threshold
under the RL action. When levees are raised in combination with
reservoir re-operation (RR+RL), slightly higher costs are projected
for EAC compared to the RL option (due to crop-damage costs
incurred by controlled ood releases); however, oodplain inunda-
tion is achieved fully as in the RR option, so that the overall domain
of mutually acceptable performance is larger than all other options
(white space in Fig.3). us, the RR+RL action would provide the
most robust management strategy for an uncertain future, that is, it
would satisfy economic (EAC) and ecological (oodplain inunda-
tion) goals over the broadest range of hydro-climate states.
Inclusion of the ow recession rate metric allows evaluation of
prospects for achieving sustainable management for more than two
Figure 3 | Two Iowa River system performance indicators mapped in a variable future climate space defined by change in annual precipitation variability
and mean annual flow for each of 4 management actions (rows). The first column shows estimated annual costs (engineering performance indicator),
expressed as values relative to the historical long-term (1959–2010) mean, with values exceeding the threshold (dashed line) of 1.5-times the historical
level (shown by colour scale) being unacceptable. The second column indicates the floodplain inundation area (ecological performance indicator), with
values falling below the threshold (dashed line) value of the historical mean (shown on colur scale at 1.0) deemed unacceptable for floodplain inundation.
The overlapping domain of mutually acceptable performance for the two indicators is shown as white space in column3.
Estimated annual costs Floodplain inundation area Mutually acceptable performance
Change in mean flow
Status quoRe-operate reservoirRaise levees
Raise levees and
re-operate reservoir
Change in precipation variability (CV)
0.81 1.2
0.81 1.2
0.81 1.2
0.81 1.2 0.811.2
Number of satisficed metrics
© 2015 Macmillan Publishers Limited. All rights reserved
metrics simultaneously (Fig.4). In general, this ecological metric
is sensitive to precipitation variability but remains below the target
threshold (+30% of historical ‘natural’ average recession rate) only
when change in precipitation variability is low and mean daily ow
is at or above 50% of the historical mean. None of the three active
management options (RR, RL or RR+RL) modify the performance
of this metric relative to the SQ option, which is perhaps not sur-
prising given Coralville’s primary design function of ood control.
Other options would need to be explored to modify ow recession
rates and enhance performance of this indicator.
By combining the ow recession rate metric with the EAC and
oodplain inundation metrics, we can project a space for all three
(Fig.4, fourth column) that shows a more constrained domain of
mutually acceptable performance compared with the previous
two-metric example (Fig.3). However, the comparison of all man-
agement options again shows that the RR+RL option provides the
largest opportunity to achieve performance objectives in an uncer-
tain future. To potentially expand the climate domain under which
the ow recession rate criterion is satised, future iterations of the
EEDS process could consider additional changes in reservoir reop-
erations (that is, restriction of ow release rates from the reservoir),
a choice that stakeholders may or may not be willing to pursue.
Overall, these ndings suggest that raising levees could provide
substantial benets in reducing ood damage under a wetter and
more variable climate future. However, in drier and less variable
future climate states, relatively low ood risks would make levees
an unwise economic investment. Similarly, the results indicate that
ecological benets of oodplain inundation from re-operation
would be realized under current and moderately wetter climate
conditions. If the climate were to shi to extreme wet or dry states,
the ecological benets of re-operation are less clear for oodplains
because in very dry years there would be insucient water available
to activate oodplains and the abundance of water in very wet years
would make the eects of dam re-operation negligible.
We recognize that all simulated climate states evaluated in the
system model are not equally plausible; however, the purpose of the
vulnerability analysis is to determine how much the climate must
change before the system is at risk of crossing key performance
thresholds in the hypothetical example presented here. Once system
failures are identied, judgments must be made regarding the plau-
sibility of the conditions causing such failure using available climate
information (such as downscaled GCMs, historical and palaeocli-
mate records, and so on) and expert opinions about other sources of
future hydrologic change (such as changes in runo from land use
change, growing human water demand, and so on). Confronting the
performance under changing temperature and precipitation with
climate change scenarios can help to identify if projected climate
change is a threat and when a tipping point57 might be reached and
require active management actions.
To place our results in the more conventional context of climate
vulnerability analysis, we used downscaled, bias-corrected cli-
mate model ensembles (from the Coupled Model Intercomparison
Projects 3 and 5; CMIP3 and CMIP566) and plotted these projec-
tions over the system response surfaces to indicate the potential
Change in mean flow
Status quoRe-operate reservoirRaise levees
Raise levees and
re-operate reservoir
Estimated annual costs Floodplain inundation area Mutually acceptable performanceFlow recession rate
Change in precipation variability (CV)
Number of satisficed metrics
0.8 1 1.2 0.8 1 1.2 0.8 1 1.2 0.8 1 1.2
0.8 1 1.2
0.8 1 1.2
0.8 1 1.2
0.8 1 1.2
0.8 1 1.2
0.8 1 1.2
0.8 1 1.2
0.8 1 1.2
0.8 1 1.2
0.8 1 1.2
0.8 1 1.2
0.8 1 1.2
Figure 4 | Three Iowa River system performance indicators mapped in a variable future climate space defined by change in annual precipitation
variability and mean annual flow for each of 4 management actions (rows). The estimated annual costs and the floodplain inundation area are as in
Fig.3.The third column is the flow recession rate indicator, with values exceeding the threshold of +30% of historical, unregulated inflow recession rates
(shown on colour scale at 1.3) being unacceptable (to the left of the dashed line). Mutually overlapping performance for all combinations of the three
indicators (one engineering and two ecological) is shown in the fourth column for each of four management actions.
© 2015 Macmillan Publishers Limited. All rights reserved
range of plausible future climate changes experienced in the Iowa
River system by 2050 (Supplementary Fig.3). ese GCM projec-
tions suggest that the system is vulnerable to climate change and that
the RR+RL action is favoured for reducing economic and ecological
risks to projected climate changes over the next several decades.
Ultimately, decision makers in this system would have to assess
the costs, benets and political will to implement new ood con-
trol alternatives. In our example, it seems that raising the levees
and changing operations confers the greatest robustness to climate
change uncertainty. Timing of decisions and rates of change of cli-
mate are issues of detail that must be addressed by policy makers
and stakeholders as they implement EEDS (or any form of adaptive
management) in real-world applications, similar to the climate-risk
planning eort undertaken in the Great Lakes32. For example, the
resources required to implement reservoir reoperations are likely
to be less than constructing new levees, as well as being reversible,
suggesting that a staged implementation approach may be appropri-
ate. is could be potentially triggered by evidence of worsening cli-
mate conditions, as has been described by the ‘adaptation pathways’
approach, an emerging policy-analysis tool67,68.
EEDS as a foundation for sustainable management
Deep uncertainty about future hydrology undermines traditional
approaches for the design and operation of water infrastructure to
achieve ‘reliable’ performance29,30 and poses an unprecedented chal-
lenge for sustaining healthy, resilient freshwater ecosystems. On
a global scale, current infrastructure (dams and irrigation works)
is extensive and a signicant driver of freshwater ecosystem deg-
radation16,60,69–71. Historical evidence clearly indicates that human
decisions on the design, location and operation (or reoperation)
of water infrastructure such as dams will have both immediate and
long-term eects on the health and resilience of freshwater ecosys-
tem function and biodiversity72,73. Given the inevitability of much
new and redesigned water infrastructure, a new spirit of coopera-
tion and collaboration among water resource engineers and con-
servation ecologists is needed to improve design and operate water
infrastructure eciently to meet both human and ecosystem needs
in a socially acceptable and sustainable way.
EEDS is a framework that can provide a transparent process
for operationalizing sustainable water management through inte-
gration of socio-environmental objectives in a decision-oriented
vulnerability assessment framework. is approach has several
strengths. First, it is designed to manage risk of uncertainty and
provide guidance to managers and decision makers by focusing on
the vulnerability of engineering and ecological indicators to a range
of hydrologic futures. It does not rely solely on downscaled GCM
projections to assess climate risks but can include a wide range of
sources of hydrologic non-stationarity, including historical and pal-
aeoclimate records and modelled land-use change information and
changing water allocations.
Second, EEDS represents only a relatively small adjustment to
the existing water management decision-making processes. e
key change is in assessing ecosystem vulnerabilities equally and
early in the design process, so that trade-os can be identied and
addressed accurately in the beginning of the planning process and
thus help inform social choices55. While engineering objectives of a
project may sometimes be perceived as irreconcilable with ecologi-
cal performance targets, it is possible that strategies for satisfying
even modest ecological objectives may improve economic perfor-
mance of water infrastructure systems, as has been shown with the
restoration of coastal wetlands for wave-surge protection74 and the
incorporation of oodplains and wetlands in ood design61. Other
non-hydrological applications of EEDS are possible, such as design-
ing and operating dams to minimize harmful distortions in water
temperature and sediment regimes that have quantiable down-
stream ecological impacts. EEDS might also be used to identify
when proposed water management designs are not compatible
with socially valued ecological features. Similarly, EEDS could con-
ceivably be applied to a range of non-aquatic engineering design
questions where engineering and ecological trade-os are signi-
cant. Regardless of the specic project context, a full exploration of
decision consequences on multiple performance indicators in a for-
mal analytical framework can promote informed and transparent
decision-making by enabling discussion about mutually satisfying
solutions in water management planning and infrastructure design.
ird, the EEDS framework can help inform a wide variety of
management decisions that need to balance ecosystem sustain-
ability with desired economic objectives. Ecological performance
objectives can be construed broadly; for example, from economi-
cally valuable sheries to a highly desirable environmental amenity
that has signicant non-market value for stakeholders. As such, the
decision framework is structured in a way that is relevant to those
who are aected by planning and decisions. e EEDS framework
is also well suited to ‘scale up’ to whole-basin planning to evaluate
how planned infrastructure projects could meet both economic per-
formance and ecosystem services under changing climate and water
development in large rivers in the developing world72.
Finally, the EEDS framework can inform decisions regarding
existing water infrastructure systems, such as reoperation of down-
stream discharge releases from dams (as illustrated in our Iowa River
case study), or decommissioning of projects. In developed countries
such as the United States, thousands of dams built in the early to
mid twentieth century no longer provide their intended benets
due to infrastructure decay, the loss of storage capacity from sedi-
ment accumulation and increased hazard risk owing to downstream
development63. e convergence of ageing infrastructure with grow-
ing concern over trends of environmental degradation is providing
unprecedented opportunities for ecosystem restoration64. However,
climate change and uncertainty about ecosystem responses to
infrastructure modication or removal make it dicult to identify
economically and environmentally acceptable strategies. Similarly,
there is growing interest in the re-operation of functioning water
infrastructure as a mechanism to buer aquatic and riparian ecosys-
tems against climate change in regulated rivers14. EEDS analysis can
provide an operational framework for evaluating the consequences
of dierent management options by explicitly quantifying trade-os
among engineering design options and environmental objectives
under plausible ranges of hydrologic non-stationarity.
Integrated water resources management for both human economic
needs and ecosystem health is increasingly recognized as essential
to societal well-being20,75. However, progress towards more sustain-
able forms of water management is hampered by conicting inter-
ests, existing economic policies, inexible infrastructure design and
a lack of quantitative, transparent tools to facilitate critical decision-
making. Debates around the construction of water infrastructure
are long-standing4,35 and will no doubt continue in the face of exten-
sive proposed dam building globally2. Our aim here is not to advo-
cate for or against the necessity of water infrastructure, but rather
to argue that, in those situations where water infrastructure will be
constructed or re-operated, a new paradigm of sustainable water
management is needed, one that can be more eectively achieved
when conservation ecologists collaboratively engage with water
resources engineers to incorporate ecosystem performance goals in
the decision-making process.
A key continuing challenge for rational water resource manage-
ment is to provide a practical approach to assist planners and deci-
sion makers in navigating complex problems and diverse interest
groups who are confronted by uncertain and changing conditions.
As eective adaptive decision-making is most likely to succeed
where stakeholders are fully engaged, we believe the EEDS oers the
© 2015 Macmillan Publishers Limited. All rights reserved
potential to serve as the foundation of a new management platform
that advances freshwater sustainability while meeting human needs
for water. Further renement could include how to accommodate
future changes in societal cost functions (for example, due to popu-
lation growth) and shis in ecological requirements under transient
climate and socio-economic conditions, as well as how to sequence
management actions in a fashion that promotes long-term success.
One promising future possibility is to link EEDS with emerging
techniques that help to identify when adaptation actions should be
taken, such as the adaptation tipping point approach57, as well as
with techniques that help to identify alternative adaptation routes,
such as dynamic adaptation pathways approaches68,76. Managing
the future will necessarily occur in an adaptive context; therefore,
equally robust monitoring and evaluation plans will be needed to
ensure that decisions are drawing upon the best available infor-
mation when evaluating the consequences of alternative decision
options and management strategies.
Received 25 February 2015; accepted 21 July 2015;
published online 14 September 2015
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We acknowledge S. Steinschneider for developing the stochastic weather generator for
the Iowa River Basin; S. Wi for the VIC hydrologic model development; D. LeFever
for support in developing the reservoir systems model; and R. Olsen for his help in
providing hydraulic modelling tools and economic information for the Coralville
Lake ood control system. Special thanks to P. Clark for artwork in Fig.1. Additional
support for C.M.B. and C.M.S was provided by the NSF CAREER Award (CBET-
1054762). e views in this article are those of the authors and do not necessarily
represent the views of the OECD or its member countries. is article has been peer
reviewed and approved for publication consistent with USGS Fundamental Science
Practices ( and we thank J. Friedman of the USGS for
his constructive comments. Any use of trade, rm, or product names is for descriptive
purposes only and does not imply endorsement by the U.S. Government. is paper
resulted from a synthesis project funded by the National Socio-Environmental Synthesis
Center (SESYNC) under National Science Foundation Award #DBI-1052875.
Author contributions
N.L.P. and J.H.M. conceived the original project. N.L.P., T.E.G. and C.M.B. led the
draing of the text. C.M.S., C.M.B., T.E.G. and N.L.P. led the case study analysis. N.L.P,
C.M.B., T.E.G., J.H.M, M.A.P., C.M.S., R.L.W., M.H., G.F.M., K.C.D. and A.B. contributed
to the intellectual content through workshop participation and writing.
Additional information
Supplementary information is available in the online version of the paper. Reprints
and permissions information is available online at
Correspondence should be addressed to N.L.P.
Competing financial interests
e authors declare no competing nancial interests.
© 2015 Macmillan Publishers Limited. All rights reserved
... As an inherent characteristic of waterway resources, the WCC contains dual attributes of nature and society, which reflect not only the supporting capacity of regional waterway resources for socioeconomic development, but also the demand degree of socioeconomic system for the waterway exploitable scale. Therefore, to improve the WCC, it is necessary to maintain consistency with the transportation demand; balance the relationship among the development intensity of waterway, ecological protection/ restoration, and flood control pressure; and reconcile the contradiction between water resources allocation and waterway development under the influence of human activities and climate change (Chorley and Kennedy, 1971;Koetse and Rietveld, 2009;Poff et al., 2016). ...
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With rapid socioeconomic development, extra demands have been placed on the waterway sustainable exploration, which are closely related to river ecological protection, flood control and comprehensive utilization of water resources. Therefore, it is theoretically and practically relevant to investigate the waterway carrying capacity (WCC) under multi-objective coordination. Based on a hierarchical indicators system framework of WCC which including four subsystems (i.e., economic-demand system, flood-control system, water-supply system and ecological-protection system), we propose a fuzzy comprehensive evaluation model of WCC, which covers a flow module, a sediment module, an ecological module and a comprehensive analysis module. This model integrates two assessment methods of comprehensive index evaluation and fuzzy-pattern recognition with analytic hierarchy process (AHP). Determining weights by the AHP method can avoid the subjectivity and errors caused by weighing a large number of indicators, while the combined two methods have a complementarity of function to more objectively reflect the carrying capacity level of different layers. The WCC of the lower Yangtze River from Hukou to Nanjing reaches was assessed, and the results suggested that the carrying capacity states of waterway are generally on a downward trajectory with the increase of waterway scale, and the carrying capacity levels of waterway for the built (in 2015) and planning scales (in 2030) are in the state of bearable or critical bearable. In a certain future period, the exploitable thresholds of channel scales in the sections from Hukou-Anqing, Anqing-Wuhu and Wuhu-Nanjing reaches are estimated to be 8.0 × 200 × 1050 m, 8.0 × 200 × 1050 m and 10.5 × 500 × 1050 m, respectively. The evaluation results are generally consistent with exiting studies, thus the proposed model is effective to identify the threshold of waterway exploitation under the restriction of multiple factors. This research can provide a reference for the evaluation of WCC in the sustainable development of similar inland waterways.
... Some authors refer to it when using local knowledge through participative approaches to foresight future scenarios and define locally relevant adaptation strategies (e.g., Bhave et al. 2014;Girard et al. 2015a), view adopted herein. Other authors consider BU as a scenario-free, robustness-based planning process; for example, in the "decision-scaling" approach (Brown et al. 2012;Poff et al. 2016;Ray et al. 2019). As for the later view, unlike the top-down method, the BU approach relies more on possibilities than on probabilities (Blöschl et al. 2013). ...
... Sixty-five of 122 case studies used more than one metric to assess and compare adaptation strategies. Each publication assessing performance using multiple metrics referred to between two and 10 metrics, most which (41 of 65 case studies) included some form of monetary metric (e.g., Groves & Sharon, 2013;Kapetas & Fenner, 2020;Kasprzyk et al., 2013;Lawrence & Haasnoot, 2017;Manocha & Babovic, 2018;Poff et al., 2016;Ramm et al., 2018aRamm et al., , 2018b. Of these 65 case studies, 12 used Pareto optimization techniques to evaluate conflicting objectives. ...
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Decision making under deep uncertainty (DMDU) approaches are well‐suited for making decisions about infrastructure to manage flooding exacerbated by climate change. One important system for climate resilience and flood management is green infrastructure, which refers to a network of natural and semi‐engineered areas that provides ecosystem functions. Green infrastructure is often characterized as a low‐regret strategy with multiple co‐benefits under uncertainty. These attributes enable green infrastructure to be an important adaptation strategy under DMDU frameworks for flood management. However, DMDU analyses that include green infrastructure are still relatively limited, perhaps due to computational or modeling complexity and other barriers. This paper identifies and reviews publications in the flood management literature that use DMDU frameworks and refer to green infrastructure adaptation strategies, in order to identify trends and inform future research. The reviewed publications are categorized according to a variety of performance metrics, climate change scenarios, DMDU metrics, and hydrologic modeling techniques, and represent several adaptation strategies applied to case studies on five continents using a range of data sources and assumptions. This paper highlights a number of solutions that can be employed to facilitate additional research at the intersection of these fields. Primary among these is the transparent documentation and use of open source models, methods, and data. Future research should also focus on communication among different stakeholders, particularly in ensuring definitions, assumptions, and data requirements are clear. These partnerships can facilitate effective application of robust strategies such as green infrastructure for urban adaptation to the effects of climate change.
... For normative preservative scenarios, quantitative evaluation methods are more practical in identifying whether an objective is accessible or not. Such approaches include scenario discover [44], [58][59][60], decision scaling [61], and adaptation tipping point approaches [19]. ...
... Under complex and changing conditions, the urban water sector should adopt practical and effective methods to meet adaptive management requirements in a changing environment. In addition, the public sector also needs to consider all relevant stakeholders' interests to trade off social, economic, and ecological benefits (Poff et al. 2016). ...
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Because of the ever-increasing impact of climate change and human activities, urban water supply systems encounter multifaceted challenges in providing sustainable services under various uncertainties. Urban water supply system resilience (UWSSR) refers to the ability of a water supply system to maintain its functional stability and adapt to changes. This study aims to analyze the spatial and temporal differences of UWSSR characteristics in the Yangtze River Delta urban agglomeration of China, as well as the contributing factors. Twelve indicators are selected to establish the evaluation framework, and the composite index is calculated using the coefficient of variation method. The spatial agglomeration and distribution characteristics are discussed based on spatial correlation analysis. The results show that (i) UWSSR does not improve significantly with time because it is mainly constrained by the extent of water resources. (ii) UWSSR has a significant spatial correlation for most years, but the spatial agglomeration pattern is not significant. (iii) UWSSR is positively influenced by public services and negatively influenced by public regulation and the level of urbanization during two successive stages. The variables whose regression coefficients changed during these stages are per capita gross domestic product, public financial resources, level of industrialization, public investment in water supply facilities, and public investment in science and technology. This means that the impact of these variables on resilience inverted from promotion to inhibition or from inhibition to promotion. Therefore, this study provides a reliable framework to evaluate the status of UWSSR and its driving factors, which can support effective management practices.
... Scientists are also challenged by the need to integrate the water quality requirement into the prescribed flow-ecology relationship, a task that is difficult to achieve without sophisticated understanding of sediment dynamics, temperature variability, and other water quality variables . In turn, water managers often face challenges in implementing environmental flow regimes that have been informed by prescribed flow-ecology relationships due to operational and infrastructure constraints e.g., dam operation schedules (Poff et al. 2016). Finally, both communities are challenged by the need for more socially robust environmental science to increase its understanding, legitimacy, and relevance to decision-making (Hickey et al. 2013). ...
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Although environmental flow regime assessments are becoming increasingly holistic, they rarely provoke water managers to enact the adaptive water reallocation mechanisms required to secure environmental water for wetlands. The conditions that cause science-based environmental flow assessments to succeed or fail in informing the management of environmental water requirements remain unclear. To begin to resolve these conditions, we used process tracing to deconstruct the sequence of activities required to manage environmental water in four case studies of seasonally ponding wetlands in Mediterranean and Mesoamerican watersheds. We hypothesized that, when the flexibility and equitability of the socioeconomic system do not match the complexity of the biophysical system, this leads to a failure of managers to integrate scientific guidance in their allocation of environmental water. Diagnostic evidence gathered indicates that science-management partnerships are essential to align institutional flexibility and socioeconomic equitability with the system’s ecohydrological complexity, and thus move from determination to reallocation of environmental water. These results confirm that institutions e.g., river basin organizations need to be supplemented by motivated actors with experience and skill to negotiate allocation and adaptive management of environmental water. These institutional-actor synergies are likely to be especially important in water scarce regions when the need to accommodate extreme hydrological conditions is not met by national governance capacity. We conclude by focusing on benefit sharing as a means to better describe the conditions for successful science-based environmental flow assessments that realize productive efficiency in environmental water allocation i.e., recognition of multiple values for both people and ecosystems.
In view of accelerated climate change and urban demographics, balancing human and ecosystem needs for water resources is a critical environmental challenge of global significance. Since water, agriculture, health, and energy are inextricably linked, sustainable development goals (SDGs) actions in one policy area commonly have impacts on the others, as well as on the ecosystems that natural resources and human activities ultimately depend upon. Managing urban water supply systems therefore requires a nexus approach that integrates goals across sectors, reduces the risk that SDG actions will undermine one another, and ensures sustainable resource use. We developed a transdisciplinary methodological framework based on a Pareto frontier analysis to define the sustainable solutions of a multi-objective optimization among four competing criteria, water provision, water quality, energy cost, and biodiversity conservation. The study was applied to three mountainous headwater basins in the Ecuadorian Andes, which provide around 30% of Quito's total water supply. We found that an optimized management of water intake structures would meet current consumption needs while reducing the probability of emergence of water pathogens and limiting the impact on aquatic biodiversity by 30% and 9% respectively, without any increase in energy costs for pumping water from other sources. Nonetheless, under future scenarios of climate change and water demand, higher energy consumption, and therefore an increase in operating costs, would be needed to meet urban demand and preserve environmental conditions. Overall, the range of Pareto optimal water supply strategies across the water-health-energy-biodiversity nexus provides valuable information for decision makers and offers support for achieving sustainable management of water resources.
The complementary operation of hydro-photovoltaic (PV) hybrid power systems has become a popular and promising management way in modern power systems. Since hydropower and PV power depend strongly on precipitation and solar energy, previous studies have recognized that climate change can affect the stability of standalone hydro or PV power and can threaten energy security. However, the vast majority of research studies stop at the impact assessment per se and are unexpanded to hybrid power systems. The objective of this study was to explore how the complementary operation of this integrated system could be affected by climate change and identify its resilience to climate change. A “climate-hydrology-operation” bottom-up framework was developed to determine the range of changes in climatic exposure leading to system success and failure. China’s Longyangxia hydro-PV hybrid power system was selected as the study site. Our analysis revealed that (1) the complementary operation of hydro and PV power reinforces the resilience of renewable energy sources to climate change since the range in climatic exposure space leading to system success is increased; (2) the management scheme of complementary operation shows superiority compared to separate operation according to stress tests in GCMs prediction information; and (3) the complementarity of the two sources remains stable regardless of climate change—that is, if precipitation decreases then sunshine duration increases, and evaporation increases while radiation increases—thereby allowing for a more consistent level of power generation than independent hydropower and PV plant. We propose, therefore, that managing hydropower and PV resources in a complementary manner can improve the resilience of hydro-PV hybrid power systems to climate change and can lead to more effective power benefits.
As an emerging solar energy utilization technology, solar redox batteries (SPRBs) combine the superior advantages of photoelectrochemical (PEC) devices and redox batteries and are considered as alternative candidates for large‐scale solar energy capture, conversion, and storage. In this review, a systematic summary from three aspects, including: dye sensitizers, PEC properties, and photoelectronic integrated systems, based on the characteristics of rechargeable batteries and the advantages of photovoltaic technology, is presented. The matching problem of high‐performance dye sensitizers, strategies to improve the performance of photoelectrode PEC, and the working mechanism and structure design of multienergy photoelectronic integrated devices are mainly introduced and analyzed. In particular, the devices and improvement strategies of high‐performance electrode materials are analyzed from the perspective of different photoelectronic integrated devices (liquid‐based and solid‐state‐based). Finally, future perspectives are provided for further improving the performance of SPRBs. This work will open up new prospects for the development of high‐efficiency photoelectronic integrated batteries. Based on the characteristics of rechargeable batteries and the advantages of photovoltaic technology, three aspects of dye sensitizers, photoelectrochemical (PEC) performance and optoelectronic integrated systems are systematically summarized. The matching problems of high‐performance dye sensitizers, strategies to improve the performance of photoelectrode PEC, and the working mechanism and structural design of multienergy optoelectronic integrated devices are mainly introduced and analyzed.
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Large dams are a leading cause of river ecosystem degradation. Although dams have cumulative effects as water flows downstream in a river network, most flow alteration research has focused on local impacts of single dams. Here we examined the highly regulated Colorado River Basin (CRB) to understand how flow alteration propagates in river networks, as influenced by the location and characteristics of dams as well as the structure of the river network—including the presence of tributaries. We used a spatial Markov network model informed by 117 upstream‐downstream pairs of monthly flow series (2003–2017) to estimate flow alteration from 84 intermediate‐to‐large dams representing >83% of the total storage in the CRB. Using Least Absolute Shrinkage and Selection Operator regression, we then investigated how flow alteration was influenced by local dam properties (e.g., purpose, storage capacity) and network‐level attributes (e.g., position, upstream cumulative storage). Flow alteration was highly variable across the network, but tended to accumulate downstream and remained high in the main stem. Dam impacts were explained by network‐level attributes (63%) more than by local dam properties (37%), underscoring the need to consider network context when assessing dam impacts. High‐impact dams were often located in sub‐watersheds with high levels of native fish biodiversity, fish imperilment, or species requiring seasonal flows that are no longer present. These three biodiversity dimensions, as well as the amount of dam‐free downstream habitat, indicate potential to restore river ecosystems via controlled flow releases. Our methods are transferrable and could guide screening for dam reoperation in other highly regulated basins.
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Energy Policy, 69 + (2014) 43-56. doi:10.1016/j.enpol.2013.10.069
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The interrelationships between water resources, food production and energy security have influenced policy for many decades so the emergence of the water-food-energy 'nexus' as a proposed new focus for water resource management is surprising. It is suggested that this focus can be understood as a consequence of the decision by developed countries to ignore agreements reached at the 1992 Rio Summit on Sustainable Development and promote instead a 'Dublin IWRM', their original lobbying platform. That approach has not helped developing countries to address food, energy and water security nor assisted global businesses to expand or to manage the risks posed to their operations by poor water management. The nexus approach begins to address these concerns by focusing on a specific 'problem-shed'. While this may disintegrate the original robust concept of integrated water management, its emphasis on what water may do for society rather than what society should do for water is a step back toward a more coherent and useful paradigm.
This book outlines the creative process of making environmental management decisions using the approach called Structured Decision Making. It is a short introductory guide to this popular form of decision making and is aimed at environmental managers and scientists. This is a distinctly pragmatic label given to ways for helping individuals and groups think through tough multidimensional choices characterized by uncertain science, diverse stakeholders, and difficult tradeoffs. This is the everyday reality of environmental management, yet many important decisions currently are made on an ad hoc basis that lacks a solid value-based foundation, ignores key information, and results in selection of an inferior alternative. Making progress - in a way that is rigorous, inclusive, defensible and transparent - requires combining analytical methods drawn from the decision sciences and applied ecology with deliberative insights from cognitive psychology, facilitation and negotiation. The authors review key methods and discuss case-study examples based in their experiences in communities, boardrooms, and stakeholder meetings. The goal of this book is to lay out a compelling guide that will change how you think about making environmental decisions. © 2012 by R. Gregory, L. Failing, M. Harstone, G. Long, T. McDaniels, and D. Ohlson. All rights reserved.
Protecting the worlds freshwater resources requires diagnosing threats over a broad range of scales, from global to local. Here we present the first worldwide synthesis to jointly consider human and biodiversity perspectives on water security using a spatial framework that quantifies multiple stressors and accounts for downstream impacts. We find that nearly 80% of the worlds population is exposed to high levels of threat to water security. Massive investment in water technology enables rich nations to offset high stressor levels without remedying their underlying causes, whereas less wealthy nations remain vulnerable. A similar lack of precautionary investment jeopardizes biodiversity, with habitats associated with 65% of continental discharge classified as moderately to highly threatened. The cumulative threat framework offers a tool for prioritizing policy and management responses to this crisis, and underscores the necessity of limiting threats at their source instead of through costly remediation of symptoms in order to assure global water security for both humans and freshwater biodiversity.
Rapid changes in flow below hydroelectric facilities result from peaking operations, where water is typically stored in a reservoir at night and released through turbines to satisfy increased electrical demand during the day. Potential impacts of these short-term, recurring disturbances of aquatic systems below dams are important considerations in hydropower development. Reduced biotic productivity in tailwaters may be due directly to flow variations or indirectly to a variety of factors related to flow variations, such as changes in water depth or temperature, or scouring of sediments. Many riverine fish and invertebrate species have a limited range of conditions to which they are adapted. The relatively recent pattern of daily fluctuations in flow is not one to which most species are adapted; thus, such conditions can reduce the abundance, diversity, and productivity of these riverine organisms. Information needs for site-specific evaluations of potential impacts at hydroelectric peaking projects are outlined, along with management and mitigation options to reduce anticipated adverse effects.
Conservation biology and restoration ecology share a common interest in maintaining or enhancing populations, communities, and ecosystems. Much could be gained by more closely integrating the disciplines, but several challenges stand in the way. Goals differ, reflecting different origins and agendas. Because resources are insufficient to meet all needs, priorities must be established. Rapid environmental changes create uncertainties that compromise goals and priorities. To realize the benefits of integration, goals should be complementary, acknowledging the uncertainties that stem from temporal and spatial dynamics. Priorities should be established using clearly defined criteria, recognizing that not everything can be conserved or restored; some form of triage is inevitable. Because goals and priorities are societal concerns, conservation and restoration must include people as part of—rather than separate from—nature. A more meaningful and integrated approach will blur disciplinary boundaries, focus on outcomes rather than approaches, and use the tools of both disciplines.
Temporary streams in California and other Mediterranean climate areas are among the aquatic habitats most altered by human actions and by invasions by alien species. They typically support novel ecosystems, defined as ecosystems dominated by new combinations of organisms in highly altered habitats. Although these new ecosystems have many attributes of the ecosystems they replaced, such as native species, they typically contain many new interactions among species. Managers need to recognize this reality to find ways to direct change towards novel ecosystems with desirable features, including native species. The concept of reconciliation ecology is a practical approach to living with the new reality; it includes actively guiding ecosystem change, as illustrated by Putah Creek, Cosumnes River, Eel River and Six Bit Gulch in California. The first three waterways are all highly altered and managed with varying degrees of success to favour desired aquatic species, whereas Six Bit Gulch experiences such extreme conditions that the original ecosystem is still largely intact. The examples illustrate that most aquatic ecosystems in California are so highly altered that attempting to restore them to an earlier condition or stable state is largely not possible. Where more or less intact systems persist, it is usually because extreme environmental conditions restrict both alien invaders and human use in small watersheds. This pattern appears to be fairly typical of streams in Mediterranean climate areas. Copyright © 2013 John Wiley & Sons, Ltd.
What is the best way to arrange dams within river basins to benefit society? Recent interest in this question has grown in response to the worldwide trend toward developing hydropower as a source of renewable energy in Asia and South America, and the movement toward removing unnecessary dams in the US. Environmental and energy sustainability are important practical concerns, and yet river development has rarely been planned with the goal of providing society with a portfolio of ecosystem services into the future. We organized a review and synthesis of the growing research in sustainable river basin design around four spatial decisions: Is it better to build fewer mainstem dams or more tributary dams? Should dams be clustered or distributed among distant subbasins? Where should dams be placed along a river? At what spatial scale should decisions be made? The following design principles for increasing ecological sustainability emerged from our review: (i) concentrate dams within a subset of tributary watersheds and avoid downstream mainstems of rivers, (ii) disperse freshwater reserves among the remaining tributary catchments, (iii) ensure that habitat provided between dams will support reproduction and retain offspring, and (iv) formulate spatial decision problems at the scale of large river basins. Based on our review, we discuss trade-offs between hydropower and ecological objectives when planning river basin development. We hope that future testing and refinement of principles extracted from our review will define a path toward sustainable river basin design. Published by Elsevier Ltd.